Research, Technology, and Innovation Policy

Public and Private investments in research, technology development, and innovation initiatives generate substantial social impacts. They produce new knowledge, strengthen the workforce, increase economic competitiveness, and enhance quality of life and social well-being. We work closely with government agencies, hospitals, clinics, scientific research organizations, foundations, and nonprofits to help them generate maximum value and knowledge from their programs and policies.

We provide technology support, technology research, analysis, evaluation expertise, policy advice, and other technical assistance. We also help clients optimize program delivery, build capacity, and identify best practices to incorporate in their strategic plans and program management.

Our interdisciplinary teams have experience working around the world with diverse organizations, e.g., Basic Science, Life Sciences, Healthcare and Medical care providers, Medical Research organizations, Pharmaceutical organizations, etc. Our client engagement is grounded in the application of rigorous methods across an array of socioeconomic contexts and research domains.

At HubBucket, we put integrity and ethics at the core and forefront of everything we do. We adhere to established laws that govern and ensure a civilized society, e.g., Human Rights, Civil Rights, Equal Rights, Women's Rights, LGBTQ Rights, Disability Rights, Veteran's Rights, etc.

Scientific and Technological advancements and innovations are major sources of economic growth and are crucial for making social and environmental development sustainable.

What is Science, Technology, and Innovation ("STI") Policy?

Although it is common to use the term STI policy as one type of policy, one could think of it as three different “ideal” types of policies; science policy, technology policy, and innovation policy—each with distinct characteristics (Lundvall & Borrás, 2005).

Science Policy

Science policy is about the promotion of the production of scientific knowledge and, as such, deals with the allocation of resources between different scientific activities. Science policy might serve different objectives from pure curiosity about understanding the world to specific military objectives such as the atomic bomb (Jaffe et al., 2015). Science policy is sometimes based upon a linear model where it is assumed that research efforts will translate more or less automatically into economic and societal outcomes.

Technology Policy

Technology policy, in contrast, focuses on promoting the development and use of specific technologies seen as being of strategic importance for the country. Technology policy is thus based upon the assumption that there are specific strategic technologies that have a major impact upon the economy and on societal objectives, and it focuses on the development and improvement of those technologies or their wider adoption. These technologies can be specific to a particular economic activity or more generic, like information and communication technologies also referred to as “general purpose technologies.”

In a sense, innovation policy incorporates science and technology policy as it aims at intervening in the innovation process as a whole; from science (exploration) to the application to specific technologies, its introduction to the market, and its wide diffusion (exploitation). Innovation policy gives attention not only to the scientific and technological content of innovations but also to the institutional framework and the wider changes that are necessary for innovations to be introduced into the market and used. It also pays attention to other forms of learning beyond science and technology that might also lead to innovations like learning by doing, using, or interacting.

Policy can then be understood as the deliberate action from governments in the economy with the aim of attaining objectives through stimulating changes in the behavior of individuals and organizations. When it comes to STI policies, the aim is to affect the rate and direction of processes within STI. When designing and applying policies, governments need to have a theory of how innovation works in general and empirical evidence of how it works in a particular country, region, or sector. Evolutionary and neoclassical economics represent two alternative theoretical framings with different implications for what type of policies governments should pursue.

 

Figure 1. The main differences between science policy, technology policy, and innovation policy. | Source: Author’s elaboration based on Lundvall and Borrás (2005).

Figure 1. The main differences between science policy, technology policy, and innovation policy. | Source: Author’s elaboration based on Lundvall and Borrás (2005).

Innovation as an Interactive Process

Innovation may be defined as a process combining existing elements of knowledge in new ways and with new knowledge as outcome. Different organizations and individuals with distinct elements of knowledge interact in the innovation process. Interactive learning takes place within organizations as well as between organizations.

Within organizations barriers between different functions and divisions (e.g., marketing, R&D, production) may block the kind of interaction that is necessary to innovate. One reason for the increasing use of management techniques based on knowledge management principles, such as job rotation and inter-divisional teams, is that it results in functional flexibility supporting innovations rooted in interactive learning. Organizational characteristics at the firm level will have a major impact on both the capacity to develop innovation and the capacity to successfully absorb technology developed by other organizations (Lam, 2004).

However important internal knowledge flows are for innovation, one very general result from innovation surveys is that firms “do not innovate alone” but in continuous interaction with suppliers, customers, knowledge institutions, and sometimes even competitors (De Bresson et al., 1991; Rothwell et al., 1974; Von Hippel, 1988). Most of the collaboration lasts for longer periods and is informal, but there are also many examples of contractual agreements where companies enter strategic alliances to develop technologies together (Mowery et al., 1996).

There are two fundamental reasons for engaging frequently in collaboration for innovation. One is the need to reduce uncertainty and to overcome information problems while the other reflects the need to share knowledge. Regarding the first, innovation is per definition an uncertain process; if the outcome of the innovation process was known in advance, it would not deserve to be called an innovation. On behalf of the producer it involves uncertainty regarding future sales of the new product; on behalf of the user it involves technological uncertainty about the actual performance of the new product/process. With a pure market, implying arm’s-length relationships and with access only to information on quantities and prices, the uncertainty on both sides would make innovation spurious (Lundvall, 1985).

The other reason for collaboration is that the growing complexity of the knowledge required to develop innovations makes it impossible for even the largest companies to rely exclusively on internal expertise. The management concept of “open innovation” refers to this fact. While neoclassical economists emphasize intellectual property rights and pure markets, business behavior often involves knowledge sharing either via formal contracts or through informal barter of information.

Given the importance of different sources of knowledge as well as of interactive learning in processes of innovation, policies designed with inspiration from evolutionary and systemic theory focus primarily on supporting capacity building, network formation, and developing support frameworks conducive to interactive learning and innovation. Government intervention in STI is seen not as a response to “market failures” but as response to “systemic failures.”2 Among those systemic failures it is common to refer to infrastructure failures, capability failures, network failures, and hard and soft institutional failures linked to formal rules as well as more informal ones (e.g., culture) among others (Chaminade & Edquist, 2010; Smith, 2000; Woolthuis et al., 2005). Overall, STI policies addressing systemic failures differ from STI policies addressing market failures, although it may be argued that they are complementary rather than substitute and necessary at different points in time (Weber et al., 2012).

Source: Oxford | Business and Management

URL: https://oxfordre.com/business/view/10.1093/acrefore/9780190224851.001.0001/acrefore-9780190224851-e-179